Aerial imaging and analysis of surface features is used in many disciplines including, for example, geography, geology, climatology, surveillance, reconnaissance, and intelligence. Imaging data may be gathered to identify the materials or “endmembers” that are present in an area of a surface under study. The materials present may be identified by performing spectral analysis of the imaging data and comparing spectral data to known spectral signatures.
Picture elements or “pixels” in the imaging data may each represent an area that includes multiple materials. When image data includes spectra of multiple materials, the image data may be referred to as “hyperspectral imaging data.” For example, a single pixel may represent several square meters of surface area, which may include a number of materials. To determine what materials are represented in the single pixel, the hyperspectral imaging data may be “unmixed” to determine an abundance of each of the materials present.
Unmixing hyperspectral imaging data can be a complex and resource-intensive operation. Thus, significant computing resources may be required to unmix hyperspectral imaging data.